Teaching Artificial Intelligence to Prevent Car Accidents

Dashboard camera software company Nexar has published the largest and most diverse dataset of road images ever released, called the NEXET Dataset, as part of its Nexar Challenge, a coding competition to help the company develop computer vision driver assistance system. Participants will use the dataset to develop models that can accurately detect the back of cars to warn drivers of potential collisions. The NEXET Dataset contains 50,000 computer annotated training images and 5,000 manually annotated images all collected from drivers using Nexar dashcams. The images are from 79 countries, taken at different times of day, and in various weather conditions.

Joshua New is a senior policy analyst at the Center for Data Innovation. He has a background in government affairs, policy, and communication. Prior to joining the Center for Data Innovation, Joshua graduated from American University with degrees in C.L.E.G. (Communication, Legal Institutions, Economics, and Government) and Public Communication. His research focuses on methods of promoting innovative and emerging technologies as a means of improving the economy and quality of life. Follow Joshua on Twitter @Josh_A_New.